Triple
T16742575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spa |
E406868
|
entity |
| Predicate | hasMineralWaterType |
P55046
|
FINISHED |
| Object | iron-rich mineral water |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: iron-rich mineral water | Statement: [Spa, hasMineralWaterType, iron-rich mineral water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMineralWaterType Context triple: [Spa, hasMineralWaterType, iron-rich mineral water]
-
A.
hasCarbonatedWater
Indicates that an entity contains or is associated with carbonated (fizzy) water as a component or ingredient.
-
B.
hasMineralSpringsType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of mineral springs.
-
C.
mineralWaterCommercialisedBy
Indicates that a specific mineral water product is marketed, distributed, or sold by a particular commercial entity or company.
-
D.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
E.
hasWaterResourceType
Indicates that an entity is associated with a specific type or category of water resource.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c3f49808190b543d8da34031f3d |
completed | April 18, 2026, 2:59 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.